Use of a quantitative structure-property relationship to design larger model proteins that fold rapidly

A quantitative structure–property relationship (QSPR)was used to design model protein sequences that fold repeatedlyand relatively rapidly to stable target structures. The specificmodel was a 125-residue heteropolymer chain subject to MonteCarlo dynamics on a simple cubic lattice. The QSPR was derivedfrom an analysis of a database of 200 sequences by a statisticalmethod that uses a genetic algorithm to select the sequenceattributes that are most important for folding and a neuralnetwork to determine the corresponding functional dependenceof folding ability on the chosen attributes. The QSPR dependson the number of anti-parallel sheet contacts, the energy gapbetween the native state and quasi-continuous part of the spectrumand the total energy of the contacts between surface residues.Two Monte Carlo procedures were used in series to optimize boththe target structures and the sequences. We generated 20 fullyoptimized sequences and 60 partially optimized control sequencesand tested each for its ability to fold in dynamic MC simulations.Although sequences in which either the number of anti-parallelsheet contacts or the energy of the surface residues is non-optimalare capable of folding almost as well as fully optimized ones,sequences in which only the energy gap is optimized fold markedlymore slowly. Implications of the results for the design of proteinsare discussed.